When metric learning is applied to cross-view applications, e.g. image retrieval [1]}, [2]}, [3]}, the model is capable of learning similar patterns in different views which may provide geometric information of the two views, e.g. the camera pose or orientation information. We conduct orientation estimation experiment to show the advantage of point-specific activation map compared with the overall activation map on providing geometric information based on cross-view patterns. In our experiment, we take street-to-aerial image geo-localization [1]}, [2]} as an example.
